Particle Swarm Optimization for Constrained Financial Portfolio Selection: An Empirical Study on the US Market

Abdallah Saib, Aboubakr Boussalem and Kadri S. Al-Shakri
Additional contact information
Abdallah Saib: University Center El Bayadh (Algeria)
Aboubakr Boussalem: University Center El Bayadh (Algeria)
Kadri S. Al-Shakri: Ajloun National Private University (Jordan)

IJEP, 2025, vol. 8, issue 02, Pages : 308-320

Abstract: This study investigates Particle Swarm Optimization (PSO) application to portfolio optimization under realistic investment constraints. Using 48 liquid assets' market data (2019-2024), we compare PSO against classical Markowitz optimization and equal-weight benchmarks. The PSO algorithm incorporates weight limits (20%), sector concentration (40%), volatility targeting (18%), and diversification requirements. Results demonstrate PSO's superior performance with Sharpe ratio of 0.9192 versus 0.7281 for constrained Markowitz and 0.7499 for equal-weight portfolios, achieving 26.2% improvement in risk-adjusted returns.

Keywords: Portfolio Optimization; Particle Swarm; Constrained Optimization; Risk Management; Sharpe Ratio (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://ijep.dz/index.php/IJEP/article/view/390 Abstract page (text/html)
https://ijep.dz/index.php/IJEP/article/download/390/363 Full text (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bjm:ijep00:v:8:y:2025:i:02:id:390

DOI: 10.54241/2065-008-002-018

Access Statistics for this article

More articles in IJEP from ALPEC The performance of Algerian economic institutions in light of international economic mobility , Boumerdes University
Bibliographic data for series maintained by BOUZID Ahmed ().